Coded Merkle Tree: Solving Data Availability Attacks in Blockchains

Yu, Mingchao; Sahraei, Saeid; Li, Songze; Avestimehr, Salman; Kannan, Sreeram; Viswanath, Pramod

doi:10.1007/978-3-030-51280-4_8

Cited by 61 publications

(124 citation statements)

References 17 publications

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“…On the other hand, we calculate a delay in the proposed scheme of O(log n). This result is coherent with current Blockchain proposals 49 where full nodes only need to perform O(log n) operations per block, with the help of data availability proofs.…”

Section: Resultssupporting

confidence: 85%

Enabling trustworthy personal data protection in eHealth and well-being services through privacy-by-design

Robles

Bordel

Alcarria

et al. 2020

International Journal of Distributed Sensor Networks

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Users are each day more aware of their privacy and data protection. Although this problem is transversal to every digital service, it is especially relevant when critical and personal information is managed, as in eHealth and well-being services. During the last years, many different innovative services in this area have been proposed. However, data management challenges are still in need of a solution. In general, data are directly sent to services but no trustworthy instruments to recover these data or remove them from services are available. In this scheme, services become the users’ data owners although users keep the rights to access, modify, and be forgotten. Nevertheless, the adequate implementation of these rights is not guaranteed, as services use the received data with commercial purposes. In order to address and solve this situation, we propose a new trustworthy personal data protection mechanism for well-being services, based on privacy-by-design technologies. This new mechanism is based on Blockchain networks and indirection functions and tokens. Blockchain networks execute transparent smart contracts, where users’ rights are codified, and store the users’ personal data which are never sent or given to external services. Besides, permissions and privacy restrictions designed by users to be applied to their data and services consuming them are also implemented in these smart contracts. Finally, an experimental validation is also described to evaluate the Quality of Experience (in terms of user satisfaction) and Quality of Service (in terms of processing delay) compared to traditional service provision solutions.

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Section: Resultssupporting

confidence: 85%

Enabling trustworthy personal data protection in eHealth and well-being services through privacy-by-design

Robles

Bordel

Alcarria

et al. 2020

International Journal of Distributed Sensor Networks

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“…Remark 1. While any erasure code can be used to encode the CMT, in this paper we focus on LDPC codes similar to [2] and provide new designs for the LDPC codes to reduce the probability of failure. Due to only making changes to the structure of the LDPC codes, we do not compromise on other performance metrics and their order-optimal solutions in [2].…”

Section: ) Cmt Constructionmentioning

confidence: 99%

“…In the rest of the paper, we assume P (l) (f,str) (s) is equal to the upper bound provided in Eqn (2). We find the light node sampling strategy by formulating a linear program (LP) in x , β (l) based on the above probabilities such that we get a lower probability of failure against the medium adversary and strong adversary compared to random sampling.…”

Section: Ldpc Code and Sampling Co-design For Medium And Strong Adversarymentioning

confidence: 99%

Overcoming Data Availability Attacks in Blockchain Systems: LDPC Code Design for Coded Merkle Tree

Mitra

Tauz

Dolecek

2021

Preprint

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<div>In blockchain systems, full nodes store the entire blockchain ledger and validate all transactions in the system by operating on the entire ledger. However, for better scalability and decentralization of the system, blockchains also run light nodes that only store a small portion of the ledger. In blockchain systems having a majority of malicious full nodes, light nodes are vulnerable to a data availability (DA) attack. In this attack, a malicious node makes the light nodes accept an invalid block by hiding the invalid portion of the block from the nodes in the system. Recently, a technique based on LDPC codes called Coded Merkle Tree (CMT) was proposed by Yu et al. that enables light nodes to detect a DA attack by randomly requesting/sampling portions of the block from the malicious node. However, light nodes fail to detect a DA attack with high probability if a malicious node hides a small stopping set of the LDPC code. To mitigate this problem, Yu et al. used well-studied techniques to design random LDPC codes with high minimum stopping set size. Although effective, these codes are not necessarily optimal for this application. In this paper, we demonstrate that a suitable co-design of specialized LDPC codes and the light node sampling strategy can improve the probability of detection of DA attacks. We consider different adversary models based on their computational capabilities of finding stopping sets in LDPC codes. For a weak adversary model, we devise a new LDPC code construction termed as the entropy-constrained PEG (EC-PEG) algorithm which concentrates stopping sets to a small group of variable nodes. We demonstrate that the EC-PEG algorithm coupled with a greedy sampling strategy improves the probability of detection of DA attacks. For stronger adversary models, we provide a co-design of a sampling strategy called linear-programming-sampling (LP-sampling) and an LDPC code construction called linear-programming-constrained PEG (LC-PEG) algorithm. The new co-design demonstrates a higher probability of detection of DA attacks compared to approaches proposed in earlier literature.</div>

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“…The object layer is commonly organized by the block layer. It uses merkleDAG [11] to maintain the connection between blocks. ObjectId can help users verify whether the data object has been modified.…”

Section: Decentralized Storage Systemsmentioning

confidence: 99%

Keyword Search in Decentralized Storage Systems

2020

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The emerging decentralized storage systems (DSSs), such as InterPlanetary File System (IPFS), Storj, and Sia, provide people with a new storage model. Instead of being centrally managed, the data are sliced up and distributed across the nodes of the network. Furthermore, each data object is uniquely identified by a cryptographic hash (ObjectId) and can only be retrieved by ObjectId. Compared with the search functions provided by the existing centralized storage systems, the application scenarios of the DSSs are subject to certain restrictions. In this paper, we first apply decentralized B+Tree and HashMap to the DSSs to provide keyword search. Both indexes are kept in blocks. Since these blocks may be scattered on multiple nodes, we ensure that all operations involve as few blocks as possible to reduce network cost and response time. In addition, the version control and version merging algorithms are designed to effectively organize the indexes and facilitate data integration. The experimental results prove that our indexes have excellent availability and scalability.

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Coded Merkle Tree: Solving Data Availability Attacks in Blockchains

Cited by 61 publications

References 17 publications

Enabling trustworthy personal data protection in eHealth and well-being services through privacy-by-design

Enabling trustworthy personal data protection in eHealth and well-being services through privacy-by-design

Overcoming Data Availability Attacks in Blockchain Systems: LDPC Code Design for Coded Merkle Tree

Keyword Search in Decentralized Storage Systems

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